Search
Now showing items 1-7 of 7
Resolving genetic heterogeneity in cancer.
(NATURE PUBLISHING GROUP, 2019-07-01)
To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the genetic landscape of most cancer types, and ...
Measuring Clonal Evolution in Cancer with Genomics.
(ANNUAL REVIEWS, 2019-08-31)
Cancers originate from somatic cells in the human body that have accumulated genetic alterations. These mutations modify the phenotype of the cells, allowing them to escape the homeostatic regulation that maintains normal ...
Subclonal reconstruction of tumors by using machine learning and population genetics.
(NATURE PUBLISHING GROUP, 2020-09-01)
Most cancer genomic data are generated from bulk samples composed of mixtures of cancer subpopulations, as well as normal cells. Subclonal reconstruction methods based on machine learning aim to separate those subpopulations ...
Catch my drift? Making sense of genomic intra-tumour heterogeneity.
(ELSEVIER, 2017-04-01)
The cancer genome is shaped by three components of the evolutionary process: mutation, selection and drift. While many studies have focused on the first two components, the role of drift in cancer evolution has received ...
Patient-derived organoids model treatment response of metastatic gastrointestinal cancers.
(AMER ASSOC ADVANCEMENT SCIENCE, 2018-02-23)
Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from ...
Identification of neutral tumor evolution across cancer types.
(NATURE PUBLISHING GROUP, 2016-03-01)
Despite extraordinary efforts to profile cancer genomes, interpreting the vast amount of genomic data in the light of cancer evolution remains challenging. Here we demonstrate that neutral tumor evolution results in a ...